The impact of seasonality on spare part demand for automobiles

In structure of road transport operating costs, expenses for purchasing and storing spare parts can account for up to 45 %. Inventory management systems are most often based on analyzing past demand. A number of factors influence the range and quantity of spare parts needed: vehicle reliability, intensity and conditions of operation, demand, inventory availability at retail networks, and other considerations. At the enterprise level, the most significant criterion for inventory management is the total cost, which includes procurement, delivery and maintenance costs. This study revealed that there is no unified method for determining the optimal stock level of vehicle spare parts. The authors found that spare parts consumption is affected by operational intensity and vehicle reliability, as well as seasonal variations. Analysis of statistical data confirmed the seasonal dependence of spare parts stock levels. This dependence can be described by a harmonic model. It was found that there are some shifts in extreme values depending on the spare part group within a single season. More accurate accounting for these shifts can reduce inventory holding costs. The proposed approach to adjusting spare parts stock level norms in the warehouse will reduce the storage period of spare parts and, consequently, increase the efficiency of inventory management. Based on the studied statistical data, this efficiency is justified by a reduction in inventory valued at 470000 rubles per year. This method of adjusting spare parts stock level norms is applicable to both service and operational enterprises.

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Publication Details

Journal
Architecture Construction Transport
Published
2025-04-16
DOI
https://doi.org/10.31660/2782-232x-2025-1-102-111
Citations
1
Primary Topic
Forecasting Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.11
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article

The impact of seasonality on spare part demand for automobiles

Н. С. Захаров, E.G. Ishkina, Yu. D. Ishkin, A. V. Rassokhin
1 citations
Architecture Construction Transport
Forecasting Techniques and Applications
2.11
article

The impact of seasonality on spare part demand for automobiles

Н. С. Захаров, E.G. Ishkina, Yu. D. Ishkin, A. V. Rassokhin
article en
1 citations

Abstract

In structure of road transport operating costs, expenses for purchasing and storing spare parts can account for up to 45 %. Inventory management systems are most often based on analyzing past demand. A number of factors influence the range and quantity of spare parts needed: vehicle reliability, intensity and conditions of operation, demand, inventory availability at retail networks, and other considerations. At the enterprise level, the most significant criterion for inventory management is the total cost, which includes procurement, delivery and maintenance costs. This study revealed that there is no unified method for determining the optimal stock level of vehicle spare parts. The authors found that spare parts consumption is affected by operational intensity and vehicle reliability, as well as seasonal variations. Analysis of statistical data confirmed the seasonal dependence of spare parts stock levels. This dependence can be described by a harmonic model. It was found that there are some shifts in extreme values depending on the spare part group within a single season. More accurate accounting for these shifts can reduce inventory holding costs. The proposed approach to adjusting spare parts stock level norms in the warehouse will reduce the storage period of spare parts and, consequently, increase the efficiency of inventory management. Based on the studied statistical data, this efficiency is justified by a reduction in inventory valued at 470000 rubles per year. This method of adjusting spare parts stock level norms is applicable to both service and operational enterprises.

Architecture Construction TransportVol. 5(1)
Giprotyumenneftegaz (Russia) (RU), Industrial University of Tyumen (RU)
Openalex Percentile: Top 15%
Forecasting Techniques and Applications
2.11
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